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What Do Artificial Orthography Learning Tasks Actually Measure? Correlations Within and Across Tasks
Author(s) -
Xenia Schmalz,
Gerd SchulteKörne,
Elisabetta De Simone,
Kristina Moll
Publication year - 2021
Publication title -
journal of cognition
Language(s) - English
Resource type - Journals
ISSN - 2514-4820
DOI - 10.5334/joc.144
Subject(s) - orthography , fluency , task (project management) , reading (process) , correlation , computer science , psychology , cognitive psychology , measure (data warehouse) , artificial intelligence , natural language processing , linguistics , mathematics , philosophy , mathematics education , geometry , management , economics , database
Artificial Orthography Learning (AOL) may act as a possible candidate to model the learning of print-to-speech correspondences. In order to serve as an adequate task, however, we need to establish whether AOL can be reliably measured. In the current study, we report the correlations between the learning of two different artificial orthographies by the same 55 participants. We also explore the correlation between AOL skill and other participant-level variables, namely Paired Associate Learning (PAL) performance, word and nonword reading ability, and age. We find high correlations between learning of two different artificial orthographies. Correlations with reading fluency and PAL are low. These results leave questions about the link between reading acquisition and AOL. At the same time, they show that AOL ability can be reliably measured and justify its use for future studies.

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